Using Graphs to Analyze High-Dimensional Classifiers.
Ofer MelnikJordan B. PollackPublished in: IJCNN (3) (2000)
Keyphrases
- high dimensional
- training data
- decision trees
- training samples
- dimensionality reduction
- graph theory
- graph theoretic
- linear classifiers
- naive bayes
- similarity search
- small sample
- supervised classification
- low dimensional
- machine learning algorithms
- test set
- directed graph
- multi dimensional
- variable selection
- training set
- sparse data
- support vector
- class labels
- svm classifier
- classification rate
- feature space
- object recognition
- multiple classifiers